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math.ST2024★ 1 cited
Large data limits and scaling laws for tSNE
Ryan Murray, Adam Pickarski
This work considers large-data asymptotics for t-distributed stochastic neighbor embedding (tSNE), a widely-used non-linear dimension reduction algorithm. We identify an appropriat…
stat.ML2024
On Probabilistic Embeddings in Optimal Dimension Reduction
Ryan Murray, Adam Pickarski
Dimension reduction algorithms are a crucial part of many data science pipelines, including data exploration, feature creation and selection, and denoising. Despite their wide util…
math.AP2024
Uniform Convergence of Adversarially Robust Classifiers
Rachel Morris, Ryan Murray
In recent years there has been significant interest in the effect of different types of adversarial perturbations in data classification problems. Many of these models incorporate…